FUNtervals – Exercise Intervals For Children
High Intensity Intervals: The key to a focused classroom? This month I have been focusing on the effects of physical exercise on academic performance in school age children. Research has demonstrated that levels of fitness are positively correlated with academic performance and research done by Fedewa et al. showed the positive effects of integrated physical exercise on performance in mathematics. For the next two articles, I decided to investigate studies that utilized acute bouts of exercise as the intervention. My reasoning for this is twofold. First, research has shown that, like extended aerobic exercise, acute bouts of exercise can produce beneficial outcomes related to memory and cognition. Secondly, high intensity intervals can be done more quickly and take up less learning time. While 30-mintues of aerobic exercise is desirable educators who are 1 9
adhering to demanding curricula likely do not have the time to allocate to extended physical exercise. Enter FUNtervals.
FUNtervals Research done by Ma, Mare, and Gurd (2016) utilized mid-day, short, highintensity interventions, which they called FUNtervals. The aim of the study was to examine the effects of these intervals on attention in students in grades 3-5. In line with findings of previous research, the present researchers hypothesized that students who engaged in the high-intensity activity would demonstrate better selective attention compared to students who did not engage in the interval training. Furthermore, they predicted that this effect would be particularly present in students who demonstrated high levels of off-task behavior. For the purpose of this study, the researchers utilized FUNtervals which were defined as “high-intensity interval activities that take only 4 minutes to complete… consisting of 20s of high-intensity activity separated by 10s of rest, repeated 8 times” (Ma, Mare, Gurd., p. 239). Examples of movements included in the FUNtervals include: 1. 2. 3. 4. 5.
Squats Jumping jacks Jumping Running Scissor kicks
The researchers utilized a single-group, repeated crossover design such that each of the students had days which they participated in the FUNtervals as well as days they did not participate in the FUNtervals. In the first week, students were acquainted with the attention tests and the FUNterval activities and researchers observed and measured off-task behavior. Off-task behavior was defined as “disengagement from the learning task at hand” (p. 239). 2 10
During the second and third weeks of the study, FUNterval and no-activity breaks were randomized and delivered on 2 separate days such that on one day, half the students participated in FUNtervals and the other half did not. Then in week three, the order was switched so that the participants who initially did FUNtervals first, now did them second.
The Observation Phase Researchers identified off-task behavior using the Behavioral Observation of Students in Schools tool definitions. Each student was observed for 5 minutes each day. Researchers noted frequency and duration of off-task behavior such as fidgeting, drawing, restlessness, talking to classmates, speaking out of turn, gazing off, failing to make eye contact with speaker etc. The d2 test of attention was used to measure selective attention. The test is made up of 14 lines of 47 characters including letters “p” and “d” with “1-4 dashes arranged individually or in pairs above or below the character” (p. 240). Students were instructed to scan the characters and mark all “d”s with 2 dashes either above or below. Students were scored on how many characters he or she was able to process in 4 minutes and 40 seconds.
The Results
Written by: Catherine O’Brien
The results demonstrated that participation in FUNtervals led to improved selective attention in 9 – 11 year olds. This improved selective attention was demonstrated by enhanced performance on the d2 task such that students made fewer errors on the d2 task on days they completed FUNtervals. Improving attention is particularly exciting when you consider that attention is the foundation on which other types of cognitive processes rely. These findings are relevant because they show an opportunity to efficiently and effectively improve classroom attention. The intervention takes up very little time thus making it more feasible and appealing for integration into daily classroom structure. My next article will dive deeper into some additional research that also supports the use of interval training as exercise intervention in the classroom.
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The Effect Of HIIT On Children’s Motor Skills In my last article, I introduced a study that utilized interval training (FUNtervals) in the classroom (Ma, Mare, & Gurd, 2015). The research demonstrated that engaging in FUNtervals had the potential to improve selective memory in children. Understanding that attention is the basis for deeper cognitive function (learning, memory etc.), I was interested in looking into research examining how intervals may affect other cognitive processes. Research done by Lundbye-Jensen, Skriver, Nielsen, and Roig (2017) investigated the effects of acute exercise on motor memory in 3rd and 4th-grade students. The aim of the study was to identify whether an acute bout of exercise following a motor skill task in the classroom could improve retention of motor memory. Previous research has demonstrated a positive relationship between motor skill function and academic achievement and between daily physical education an improved motor skill performance. As previously discussed, interval training has been shown to produce many of the same beneficial cognitive effects as extended aerobic exercise. Given the previous research in the space, the present researchers designed a study to measure the effects of two types of high-intensity training on motor memory in children. Participants were 78 diverse children in 3rd or 4th grade. Participants were randomly assigned to one of three conditions- running (RUN), floorball (FLB) or control (CON). In order to help control for differences between the groups, each of the three groups were matched on gender, age, BMI, and fitness level. Throughout the experiment, subjects participated in 4 separate sessions.
4 Sessions: • Session 1: pre-examination session including aerobic fitness testing (measuring VO2max) • Session 2: Subjects practiced the motor memory task • Session 3: Participants engaged in running (RUN), floorball (FLB) or nothing (CON) based on his or her assigned condition for 20 minutes. This session took place immediately after the practice motor task session. * 4 1
• Session 4: Retention tests were run 1-hour, 24-hours and 7-days post initial practice of motor task. *All subjects rested for 40 minutes upon completion of the intervention (RUN, FLB, CON). The motor memory task was designed using customized software. Participants were seated in front of a computer screen and asked to control the cursor with his or her dominant hand. The cursor moved vertically and horizontally. After one minute of familiarization with the feel of the cursor and the associated movement of the arrow on the screen, the acquisition task initiated. In this task, subjects were instructed to match the cursor as accurately as possible to the preset target. All targets required that the subjects move the cursor both vertically and horizontally. Motor performance was measured based on the root mean square error (RMSE) between the preset target and the subjects’ trace. Between each of the 8 targets presented, the cursor was positioned at “target mean” in the middle of the screen. In this way, subjects always started and ended at the same central location. “Their score was defined as the mean of absolute vertical errors between the cursor and target in relation to target mean. If the error exceeded two times the distance from target to target mean, the score for this data point was set to zero.” (p.183).
Three Rounds: Each subject completed blocks of 24 trials including three rounds of the eight different targets. Each trial was followed by a pause in which the subject received feedback regarding: 1. Knowledge of result – i.e. their score from 0-100 2. Knowledge of performance- which included a picture that showed the subjects’ trace and the target and 3. Average scores so children understood how his or her scores compared to the average performance. In the FLB condition, students played a game of floorball. The structure of the game was as follows, 2-minute instructions, 3-minute low intensity warm up followed by 3-minute high-intensity play and then 2-minutes of low-intensity play. They continued to switch between 3-minute high-intensity play and 2-minute low-intensity play for the duration of the game. 5 2
The children in the RUN condition participated in a similar protocol including instructions and warm up and alternating 3-minute high intensity running with 2-minute low intensity running. In both the FLB and RUN conditions, subjects completed 9 total minutes of high-intensity activity. Subjects in the CON condition were instructed to sit comfortably and had the opportunity to watch cartoons. Subjects HR was monitored using a Polar tea 2 system heart monitor. After completing their designated intervention, participants all rested for 40-minutes. They then completed another motor memory task 1-hour, 24-hours, and 7-days post intervention. The purpose of measuring performance at multiple points in time was to understand when the motor memory associated with the task was consolidated.
Motor Skills: Baseline analyses revealed no significant difference between subjects’ motor skills prior to intervention suggesting that all students had comparable performance on the initial motor memory test. Results revealed that engaging in an acute bout of exercise did indeed improve long term motor memory. Interestingly, the positive effects were only present in the delayed testing that occurred 7-days post intervention (See Figure). Subjects in the RUN and the FLB groups both demonstrated improvements suggesting that the type of high-intensity training did not affect the outcome.
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Previous research has demonstrated that high-intensity exercise may diminish performance on memory tasks when the tasks are performed immediately or soon after the exercise intervention. There could be various reasons, for example, subjects may be overly aroused upon completing the exercise bout and thus unable to focus. The researchers of the present study posit that the increased performance 7-days post intervention may be attributed to a longer memory consolidation process. f you are like me, you may be thinking, is it possible that the motor memory improved due to practice? That is, subjects experienced the motor memory task pre intervention, 1-hour post, 24-hours post and 7-days post. This is where the control group comes in. Because the control group did not experience the same improvements at 7-days post compared to those in the RUN and FLB groups, we can infer that the improvements were not due to practice effects and were caused by the high-intensity intervention.
Take Aways: So what do these findings mean? The present research successfully builds upon previous work demonstrating the powerful cognitive benefits associated with high-intensity interval training. As discussed in my previous article on a protocol using FUNtervals, high-intensity training had positive effects on selective attention in school age children. Given that attention is the foundation for learning and memory, it is exciting to see this concept applied to a deeper cognitive process (attention vs. memory). From my point of view, the key takeaway is that intervals have the potential to improve selective attention and memory in children. The effects on memory, according to the present study, are more long term and less immediate, however. As such, employing a steady regimen involving interval training could perhaps improve academic performance related to motor memory over time.
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Study Shows Active Children Are Better At Math
We know that aerobic exercise has positive effects on brain health and cognition. Recently, a greater emphasis has been placed on the relationship between aerobic exercise and brain health in the developmental years. From a structural point of view, greater physical activity has been associated with increased volume of the hippocampus and dorsal striatum. Previous research has also provided evidence that cortical thinning, which occurs during development, is associated with improved intellectual functioning. Based on previous findings, the present researchers were interested in exploring the relationship between aerobic fitness level, academic achievement and cortical thickness in children age 9-10. They hypothesized that greater levels of physical fitness would be positively associated with cortical thickness and that cortical thinning would be associated with brain maturation and development. As such, they predicted that the high fit children would demonstrate decreased cortical thickness which would relate to stronger performance on the Wide Range Achievement Test. 8 5
Sample Size: Children ages 9-10 were screened using The Kaufman Brief Intelligence Test. Participants were excluded if their scores fell more than 1 standard deviation below the mean or above the 85th percentile. They also determined participants distance away from puberty / developmental stage using the Tanner Staging System. All participants completed a test of cardiopulmonary fitness (VO2max) to determine his or her fitness. During this test, participants ran on a treadmill at a steady pace while the incline was increased by 2.5% every 2 minutes. The grade of the treadmill increased every two minutes until the participant expressed that he or she could no longer continue. “VO2 max was defined when oxygen consumption remained at a steady state despite an increase in workload” (Chaddock-Heyman et al., p. 11). Participants were assigned to either the low or high fit groups based on their fitness test results. If participants performed above the 70th percentile, they were considered “high” fit. If participants performed below the 20th percentile, they were considered to be “low’ fit. All participants who did not fall into either of these categories were excluded from the study. One way to measure cortical structures on living subjects is to calculate cortical thickness by measuring the distance between the brain’s gray/white matter boundaries and pial surfaces (Chaddock-Heyman et al., p.2). In order to measure cortical thickness, participants were placed in a high-resolution MRI machine where a series of measurements and the images were collected on a 3-T head-only Siemens Allegra MRI scanner. In order to measure academic achievement, participants completed the Wide Range Achievement Test (WRAT-3). This test included measures of reading, spelling and arithmetic abilities.
The Results: They performed a series of statistical analyses to compare demographic and physical fitness measures. They also analyzed relationships between fitness level (high vs. low) and cortical thickness. Finally, they conducted analyses to examine the relationship between cortical thickness and academic achievement. In line with the researcher’s hypothesis, the high fit children “showed decreased gray matter 9 6
thickness in the superior frontal cortex, superior temporal areas, and lateral occipital cortex� (p. 7). This higher fitness level and lower cortical thickness was also associated with superior achievement in mathematics on standardized achievement tests when compared to lower fit children. The results demonstrated a positive relationship between aerobic fitness, cortical thinning and performance in mathematics (see figure below). That is, increased aerobic fitness was positively correlated with increased performance on the WRAT arithmetic test and decreased cortical thickness was positively correlated with increased performance on the WRAT arithmetic test. Given the results showed correlations for math performance only, Chaddock-Heyman et al. point out that their findings show the need for further investigation to better understand the different biomarkers associated with academic achievement in various areas (mathematics, spelling, verbal).
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Take Aways: This study demonstrated an important association necessary to further investigate the relationship between aerobic exercise and academic achievement. I particularly appreciate the methods of this study that incorporated cortical thickness measurements. While, in my opinion, behavioral outcomes are of the utmost importance, anatomical differences and changes associated with aerobic exercise are also noteworthy. The positive relationships observed in this study create an excellent foundation for future research on the subject. The findings of this study, in their correlational nature, leave some questions unanswered, however. While the researchers took measures to control for extraneous variables (Socioeconomic status, IQ etc.) the correlational nature of the study prevents one from garnering causal results. In this way, a follow-up study using a randomized control design is necessary. My next article will delve into research which tackles this very topic.
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Kids Need To Move To Improve
In my previous article, Study Shows Active Children Are Better At Math, I discussed research that demonstrated a positive relationship between physical fitness and academic performance in children. As a quick refresher, the research I discussed was conducted by Chaddock-Heyman et al. (2015) and found positive relationships between children’s level of fitness (high vs. low) and his or her performance on an arithmetic test. While these findings are exciting, the correlational style of the study prevents us from determining causation. That is, in the absence of a randomized control design, causality cannot be assumed. Given this, I did some research and came across a study that aimed to tackle this subject using a randomized control design. Research done by Fedewa, Ahn, Erwin and Davis (2015) examined whether participation in extracurricular physical activity during the school day promoted academic gains for children. The aim of their study was to test whether physical activity breaks during the school day had a positive effect on fluid intelligence and academic achievement. Previous research done by Reed et al. (2010) found that 12
physical activity breaks did indeed improve fluid intelligence. Fedewa, Ahn, Erwin and Davis employed the same definition of fluid intelligence as was used in other studies. Fluid intelligence is defined as “the ability to reason quickly and abstractly” (Fedewa et al. p, 137). Fedewa et al. stress that fluid intelligence does not rely on one’s ability to acquire knowledge through experience but is a more generalizable type of intelligence that measures problem-solving ability and logical thinking.
The Participants Participants for the study were children from four urban schools currently in third, fourth, or fifth grade. Using random assignment, two of the schools were assigned to be the experimental condition and two to be the control condition. The sample was made up of 460 students in grades 3,4 or 5. The control classrooms included 304 students and the experimental classrooms included 156 students. The students were taught by the same individual teachers for the duration of the study. The study took place over the course of the academic year from September to April. They hypothesized that students in the experimental classrooms using physical activity breaks would experience statistically significant increases in fluid intelligence and academic achievement in mathematics and reading compared to students in the control classrooms.
The Study: In the experimental condition, physical activity was incorporated into daily activities for 20-minutes / day, 5 days a week. Interestingly, the physical activity was not a separate part of the day but rather integrated into the lesson. The teachers were equipped with ‘standardized movement cards’ which provided “aerobic-based activities that were developmentally-appropriate (i.e. the activities were unique for upper or lower elementary school-aged youth)” (p.138). Some examples of the activities included having children do jumping jacks with mathematical facts, or finding different decks of cards that are spread around the classroom (i.e. the teacher calls out a letter, color, or number and students move around the room trying to find the designated card). In the control classrooms, the teachers taught lessons as usual. In order to measure physical activity, all students wore a pedometer. They were given instructions on how to wear the pedometer and each participant was instructed to test the pedometer and walk 50 steps. If the pedometer reported a step count that 13
that was more than 10% different from 50 steps, they were issued a new pedometer until the step count fell within the acceptable range of error. In addition to monitoring the step count differences between experimental and control groups, the researchers were interested in the difference in steps between the experimental and control groups but were also interested in the potential effects of seasonality. That is, did children take more or fewer steps in certain seasons (fall, winter, spring).
Teacher Training: They utilized the Standard Progressive Matrices Test (SPM) to measure fluid intelligence. The SPM was administered by classroom and took approximately 45 minutes. The students took the test two weeks prior to the intervention and then again two weeks after the intervention ended. Academic achievement was measured by performance on mathematics and reading scores on a standardized test. Once again, students took the standardized test prior to the intervention and again after the intervention was completed. In order to ensure the teachers in the experimental exercise group were equipped to carry out the study, they attended two training sessions. These training sessions instructed teachers on how to incorporate physical activity into their lessons, how to use movement cards in the classroom, and how to log physical activity breaks. The results were quite interesting. They found a significant difference in step count between seasons such that all students took fewer steps during the winter time. This finding was contrary to Fedewa et al.’s expectations. They posited that teaching style, classroom structure, and movement in the classroom did not vary season to season and, as such, neither would step count. However, their finding suggests that seasons may play a role in the degree of movement in school age children. In this way, it may be beneficial for schools and educators to make extra effort to incorporate physical activity in the winter months. Students in the experimental condition classrooms showed statistically significant increase in mean fluid intelligence from fall to spring. The Scholastic achievement also improved from fall to spring as students in the experimental condition demonstrated significant increases in mathematics scores. In the control classrooms, fluid intelligence also increased fall to spring. Scholastic achievement in mathematics and reading, however, decreased slightly from fall to spring. 14
Fluid Intelligence: One of the interesting and unexpected findings of this study was that fluid intelligence did not improve as a result of physical activity breaks. Both the experimental and control classrooms experienced improvements in fluid intelligence suggesting the physical activity intervention was not the source of the improvement. This represented a contrast to the findings of other studies that found physical exercise interventions did support improve fluid intelligence. Fedewa et al. point out that the methodologies and the type of physical exercise may be responsible for the differences in the results. Other research protocols included running and jumping as methods of physical exercise whereas the present study used standardized motion cards. It is plausible that the type of exercise and the duration impacted the results. In my opinion, I think the protocol from the present study could be improved by using more standard methods of aerobic exercise and increasing the length of the daily intervention. That is, rather than doing 5 minutes of jumping jacks while reciting math facts, doing 20-30 minutes of jogging. I think the aim of the study to integrate the physical exercise into the lesson was an interesting one but I wonder if this could also have potentially contributed to some of the lacking results. It is possible that the students were over stimulated or cognitively exhausted upon pairing the physical with the mental. Additional research and investigation is needed in order to determine why the physical activity breaks did not have the same impact in this study as they have in others. Importantly, the physical activity breaks had no negative impacts on academic performance or fluid intelligence. Given this, educators should maintain an open mind about including physical activity breaks throughout the school day.
The takeaways: • Students moved less (as measured by the pedometer) in the winter. Educators should take measures to compensate for this decreased activity by finding more ways to get students moving in the classroom during winter months • Physical activity breaks using standardized movement cards did not have any positive impact on fluid intelligence. However, there was no negative outcome associated with the physical activity breaks suggesting there is no drawback to including physical activity breaks in the classroom. 15
•Physical activity breaks effectively increased student performance in mathematics. •The incorporation of physical activity into the lesson could have diminished the effect of the aerobic activity. Regular physical activity breaks unrelated to classroom lessons may have been more effective.
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References Lundbye-Jensen, J., Skriver, K., Nielsen, JB., and Roig, M. (2017). Acute exercise improves motor memory consolidation in preadolescent children. Frontiers in Human Neuroscience, 11:182. Ma, J.K., Mare, L.L., Gurd, B.J. (2015). Four minutes of in-class high-intensity interval activity improves selective attention in 9- to 11-year olds. Applied Physiology, Nutrition, and Metabolism, 40: 238-244. Fedewa, A.L., Ahn, S., Erwin, H. and Davis, M.C. (2015). A randomized controlled design investigating the effects of classroom-based physical activity on children’s fluid intelligence and achievement. School Psychology International, 36(2), 135153.
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